{
    "info": {
        "author": "Piti Ongmongkolkul",
        "author_email": "piti118@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Mathematics",
            "Topic :: Scientific/Engineering :: Physics"
        ],
        "description": "probfit\n-------\n\n*probfit* is a set of functions that helps you construct a complex fit. It's\nintended to be used with `iminuit <http://iminuit.readthedocs.org/>`_. The\ntool includes Binned/Unbinned Likelihood estimator, :math:`\\chi^2` regression,\nBinned :math:`\\chi^2` estimator and Simultaneous fit estimator.\nVarious functors for manipulating PDF such as Normalization and\nConvolution(with caching) and various builtin functions\nnormally used in B physics is also provided.\n\n.. code-block:: python\n\n    import numpy as np\n    from iminuit import Minuit\n    from probfit import UnbinnedLH, gaussian\n    data = np.random.randn(10000)\n    unbinned_likelihood = UnbinnedLH(gaussian, data)\n    minuit = Minuit(unbinned_likelihood, mean=0.1, sigma=1.1)\n    minuit.migrad()\n    unbinned_likelihood.draw(minuit)\n\n\n* `MIT <http://opensource.org/licenses/MIT>`_ license (open source)\n* `Documentation <http://probfit.readthedocs.org/>`_\n* The tutorial is an IPython notebook that you can view online\n  `here <http://nbviewer.ipython.org/urls/raw.github.com/scikit-hep/probfit/master/tutorial/tutorial.ipynb>`_.\n  To run it locally: `cd tutorial; ipython notebook --pylab=inline tutorial.ipynb`.\n* Dependencies:\n   - `iminuit <http://iminuit.readthedocs.org/>`_\n   - `numpy <http://www.numpy.org/>`_\n   - `matplotlib <http://matplotlib.org/>`_ (optional, for plotting)\n* Developing probfit: see the `development page <http://probfit.readthedocs.io/en/latest/development.html>`_",
        "description_content_type": "",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/scikit-hep/probfit",
        "keywords": "",
        "license": "",
        "maintainer": "",
        "maintainer_email": "",
        "name": "probfit",
        "package_url": "https://pypi.org/project/probfit/",
        "platform": "",
        "project_url": "https://pypi.org/project/probfit/",
        "project_urls": {
            "Homepage": "https://github.com/scikit-hep/probfit"
        },
        "release_url": "https://pypi.org/project/probfit/1.1.0/",
        "requires_dist": null,
        "requires_python": "",
        "summary": "Distribution Fitting/Regression Library",
        "version": "1.1.0"
    },
    "last_serial": 4457323,
    "releases": {
        "1.0.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "d66c8030cb9978a226652a01a017d2aa",
                    "sha256": "8b244a18e236226bba27cdb04439515d43c414fbe879f671e950ba6c3a4617d1"
                },
                "downloads": -1,
                "filename": "probfit-1.0.0.tar.gz",
                "has_sig": false,
                "md5_digest": "d66c8030cb9978a226652a01a017d2aa",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 723193,
                "upload_time": "2012-12-27T17:44:35",
                "url": "https://files.pythonhosted.org/packages/f7/37/7d36f60612adac02f612dec5e203e696f7dd67eafc90bc6fe166b1003164/probfit-1.0.0.tar.gz"
            }
        ],
        "1.0.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "f062f40440ca49d3639bca2306192191",
                    "sha256": "6c3571fd2a7d9245f888f4133902c4dd60329f5c9123cc5808ddfbde4dcde119"
                },
                "downloads": -1,
                "filename": "probfit-1.0.1.tar.gz",
                "has_sig": false,
                "md5_digest": "f062f40440ca49d3639bca2306192191",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 753982,
                "upload_time": "2013-01-02T23:45:06",
                "url": "https://files.pythonhosted.org/packages/6f/3a/101406a1c766a4cf949b1d7b8c9d137060a057532a4d2d926fcbf3c793c6/probfit-1.0.1.tar.gz"
            }
        ],
        "1.0.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "4669db2e9aef19392e11c7c18ffdf2e8",
                    "sha256": "55ee00d50cd1df6cc943b347a276822bb76ba6d1db5d660fd606192e806529fc"
                },
                "downloads": -1,
                "filename": "probfit-1.0.2.tar.gz",
                "has_sig": false,
                "md5_digest": "4669db2e9aef19392e11c7c18ffdf2e8",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 754807,
                "upload_time": "2013-01-06T00:43:03",
                "url": "https://files.pythonhosted.org/packages/f0/9f/c462505ae84c65f439a8cd46e5d93eb26aebbefa87f58fe663090bf7cd3a/probfit-1.0.2.tar.gz"
            }
        ],
        "1.0.3": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "b90702a14efb818eb33919b5691ac3b6",
                    "sha256": "9120fe64741cadcb6164ca6921dec176f8e81f826f63066c10a8dd159618eeb2"
                },
                "downloads": -1,
                "filename": "probfit-1.0.3.tar.gz",
                "has_sig": false,
                "md5_digest": "b90702a14efb818eb33919b5691ac3b6",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 771470,
                "upload_time": "2013-01-25T23:42:11",
                "url": "https://files.pythonhosted.org/packages/55/29/3399e93aef6d33235625c959f54644a6089733767af99c58ab64a386d5f4/probfit-1.0.3.tar.gz"
            }
        ],
        "1.0.4": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "e6f77bb7ba69bcdfcf784bbc67eef755",
                    "sha256": "a4eb2d8a171e008179c411c4c72a5413668bac7be9ac47015a7e81c2c022879e"
                },
                "downloads": -1,
                "filename": "probfit-1.0.4.tar.gz",
                "has_sig": false,
                "md5_digest": "e6f77bb7ba69bcdfcf784bbc67eef755",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 960490,
                "upload_time": "2013-06-04T18:00:13",
                "url": "https://files.pythonhosted.org/packages/31/74/75f28c372accc2176d030e3c623764810b22fb74b534b3d2e9170f4c8420/probfit-1.0.4.tar.gz"
            }
        ],
        "1.0.5": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "7b867242904c61e61e4fdf3773bda392",
                    "sha256": "8831eee5e7418ecc852b56e0233e3159cf2d86372b4156925790492825a5e35b"
                },
                "downloads": -1,
                "filename": "probfit-1.0.5.tar.gz",
                "has_sig": false,
                "md5_digest": "7b867242904c61e61e4fdf3773bda392",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 960733,
                "upload_time": "2013-09-14T22:37:13",
                "url": "https://files.pythonhosted.org/packages/80/2c/0abaeede057064b1eacbdb839f33b88693c3e0f3d78a405e1e0d5a8b446b/probfit-1.0.5.tar.gz"
            }
        ],
        "1.1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "3a852d6bee0ccfebacf6f9d3ad581803",
                    "sha256": "f185676cdaea52e41ec354b4113b0dfd14ca442aae9e0bd46ab449157f1af98d"
                },
                "downloads": -1,
                "filename": "probfit-1.1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "3a852d6bee0ccfebacf6f9d3ad581803",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1248467,
                "upload_time": "2018-11-06T13:15:52",
                "url": "https://files.pythonhosted.org/packages/9c/0e/3adcb85031548bc0d605346e41cbd4a2c4dfc45861ea077d8fa6edc1924e/probfit-1.1.0.tar.gz"
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "3a852d6bee0ccfebacf6f9d3ad581803",
                "sha256": "f185676cdaea52e41ec354b4113b0dfd14ca442aae9e0bd46ab449157f1af98d"
            },
            "downloads": -1,
            "filename": "probfit-1.1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "3a852d6bee0ccfebacf6f9d3ad581803",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 1248467,
            "upload_time": "2018-11-06T13:15:52",
            "url": "https://files.pythonhosted.org/packages/9c/0e/3adcb85031548bc0d605346e41cbd4a2c4dfc45861ea077d8fa6edc1924e/probfit-1.1.0.tar.gz"
        }
    ]
}